Sk8er & Perebor
Sk8er
Yo, I heard there's a new app that maps the best skate spots using heat maps—looks like a data puzzle. Think you'd want to dig into how it calculates the hotspots?
Perebor
Sure thing, let’s crack the heat‑map code. Do you know if it pulls raw GPS data, uses clustering, or just tallies visit counts? If we can get the dataset, we can reverse‑engineer the hotspot logic and see how they rank the spots.
Sk8er
Yeah, most of them pull raw GPS traces, then run a clustering algorithm to group rides and create those glowing spots. It’s usually a mix of visit counts and how long people hang around, so you can spot the real “hubs” where the streets buzz. If you can snag the data, we’ll reverse‑engineer the weights and see what makes a spot pop. Let's grab it and get our wheels rolling on that map.
Perebor
Sounds like a classic data puzzle. If we can pull the raw GPS logs, I’ll slice the clusters and run a quick weighted analysis—visit count plus dwell time, then tweak the coefficients until the heat map lines up with real‑world buzz. Let’s get the dataset and start hunting for the pattern.
Sk8er
Sounds dope. If you can snag the raw GPS logs from the app’s API or from a public dataset, just dump ‘em in a CSV and we’ll get to clustering. I can hook you up with a quick script to do K‑means or DBSCAN, then we’ll add dwell time as a weight. Let me know what format you’re working with, and we’ll tweak the coefficients until the heat‑map vibes with what you see on the streets. Let's do it.